Image_scatter.py

from sklearn.manifold import TSNE
tsne = TSNE(
    n_components=2,
    init='random', # pca
    random_state=101,
    method='barnes_hut',
    n_iter=500,
    verbose=2
).fit_transform(img_mat)

from matplotlib.offsetbox import OffsetImage, AnnotationBbox
def imscatter(x, y, images, ax=None, zoom=0.1):
    ax = plt.gca()
    images = [OffsetImage(image, zoom=zoom) for image in images]
    artists = []
    for x0, y0, im0 in zip(x, y, images):
        ab = AnnotationBbox(im0, (x0, y0), xycoords='data', frameon=False)
        artists.append(ax.add_artist(ab))
    ax.update_datalim(np.column_stack([x, y]))
    ax.autoscale()
    #return artists

nimgs = 500
plt.figure(figsize=(13,10))
imscatter(tsne[0:nimgs,0], tsne[0:nimgs,1], [plt.imread(image_paths[i]) for i in range(nimgs)])